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Syllabus for M.Sc.Engg.(CSE)

Computer Science and Engineering Discipline, Khulna University

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Khulna University, Khulna

Science, Engineering and Technology School

Computer Science and Engineering Discipline

Master of Science in Computer Science and Engineering, abbreviated as M.Sc.Engg.(CSE)

Grand Summary

Type of M.Sc.Engg.(CSE) Taught Credits

(Minimum)

Thesis/Project

Credits

Total Credits

(Minimum)

Research Based 18.00 18.00 36.00

Coursework Based 30.00 6.00 36.00



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Khulna University, Khulna

Science, Engineering and Technology School

Computer Science and Engineering Discipline

Summary of Courses for the Degree of M.Sc. Engg. (CSE)

(Effective from Academic Session: 2010-2011)

Course

No.

Course Title Specialized Areas Credits

CSE 5000 Scientific Research Methodology Compulsory 1.50

CSE 5001 Seminar 1.50

CSE 6000* Master Thesis I: Research Proposal 6.00

CSE 6001* Master Thesis II: Research 12.00

CSE 6002* Master Project 6.00

CSE 5101 Advanced Algorithms Theoretical

Computer Science

3.00

CSE 5102 Combinatorial Optimization 3.00

CSE 5103 Graph Theory 3.00

CSE 5104 Computational Geometry 3.00

CSE 5105 Bioinformatics Algorithms 3.00

CSE 5106 Stringology 3.00

CSE 5107 Mathematical Programming 3.00

CSE 5108 Petri Net Theory and Modeling of Systems 3.00

CSE 5151 Cryptography 3.00

CSE 5201 Advanced Software Engineering Software

Engineering and

Information

Systems

3.00

CSE 5202 Software Project Management 3.00

CSE 5203 Software Testing and Quality Assurance 3.00

CSE 5204 Software Validation and Verification Tools 3.00

CSE 5251 Advanced Database Systems 3.00

CSE 5252 Information System Management 3.00

CSE 5301 Computer Communications and Networks Communications

and Computer

Networks

3.00

CSE 5302 Wireless and Mobile Communication

Networks 3.00

CSE 5303 Wireless Ad-hoc Networks 3.00

CSE 5304 Wireless Sensor Networks 3.00

CSE 5305 Wireless Resource Management 3.00

CSE 5306 Network Security 3.00

* A student will either do M.Sc. Thesis (CSE 6000 and CSE 6001) or M.Sc. Project (CSE 6002). A student

cannot register course CSE 6001 without completing CSE 6000.



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CSE 5401 Advanced Artificial Intelligence Intelligent Systems 3.00

CSE 5402 Fuzzy Systems 3.00

CSE 5403 Machine Learning 3.00

CSE 5404 Advanced Pattern Recognition 3.00

CSE 5405 Speech Recognition 3.00

CSE 5406 Machine Translation 3.00

CSE 5407 Knowledge Representation and Reasoning 3.00

CSE 5408 Data Mining 3.00

CSE 5451 Evolutionary Algorithms 3.00

CSE 5452 Neural Networks 3.00

CSE 5501 Multimedia Systems Multimedia

Technology

3.00

CSE 5502 Computer Graphics and Animation 3.00

CSE 5503 Human Computer Interaction 3.00

CSE 5504 Multimedia Communication 3.00

CSE 5601 Parallel Algorithms High Performance

Computing

3.00

CSE 5602 Distributed Computing Systems 3.00

CSE 5603 Distributed Databases 3.00

CSE 5604 Ubiquitous Computing 3.00

CSE 5701 Advanced Microprocessors Hardware Systems 3.00

CSE 5702 Advanced Logic Design 3.00

CSE 5703 Computer Organization and Design 3.00

CSE 5704 Advanced Computer Architecture 3.00

CSE 5705 Embedded Systems 3.00

CSE 5999 Special Topic on X**

Special Topic 3.00

** Here, ‘X’ will be a complete course name offered by the course teacher.



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CSE 5000: Scientific Research Methodology

Credit Hour: 1.50

Prerequisite: None

Nature of the research process, types of research, ethics of research: voluntary participation,

anonymity and confidentiality, deceiving subjects, analysis and reporting; research proposal,

planning, purposes of research: exploration, description, explanation, ‘hard-data’ focus, ‘soft-

data’ focus, conceptualization; some practical considerations: time, venue, instrument to be used

etc, research team, interviewers, willingness of respondents to participate; data collection: four

levels of evaluation, levels of data collection/unit of analysis; research methods and tools:

interviews, group techniques, observation, questionnaires, company records/archive/information,

self-generated measures; sampling; data analysis and interpretation: quantitative analysis,

qualitative analysis; report writing: academic writing, technical writing; feedback sessions.

Computer Science Research Approaches. Theoretical vs. Empirical Methods in Computer

Science. Theoretical Models in Computer Science. Theoretical Problems in Computer Science.

Deductive Methods in Computer Science. Inductive Methods in Computer Science.

Recommended References

1. Research Methodology: A Step-by-Step Guide for Beginners, Ranjit Kumar, SAGE

Publications Ltd, 3rd Edition, 2010.

2. Research Methods for Science, Michael P. Marder, Cambridge University Press, 1st

Edition, 2011.

3. An Introduction to Scientific Research, E. Bright Wilson, Dover Publications; Rev Sub

Edition, 1991.

CSE 5001: Seminar

Credit Hour: 1.50 (Three lecture sessions in a fortnight)

Prerequisite: None

Participants will work individually to prepare reviews of papers/topics assigned by course

teacher and present before audience.



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Theoretical Computer Science

CSE 5101: Advanced Algorithms

Credit Hour: 3.00

Prerequisite: None

Randomized Algorithms: Las Vegas and Monte Carlo Algorithms; Randomized Data Structures:

Skip Lists; Amortized Analysis: Different methods, Applications in Fibonacci Heaps; Lower

Bounds: Decision Trees, Information Theoretic Lower Bounds, Adversary Arguments;

Approximation Algorithms: Approximation Schemes, Hardness of Approximation; Fixed

Parameter Tractability: Parameterized Complexity, Techniques of designing Fixed Parameter

Algorithms, Examples; Online Algorithms: Competitive Analysis, Online Paging Problem, k-

server Problem; External Memory Algorithms; Advanced Data Structures: Linear and Non-linear

Methods


1. Introduction to Algorithms - Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest

and Clifford Stein, MIT Press, 3rd Edition, 2009.

2. The Design of Approximation Algorithms, David P. Williamson, David B. Shmoys,

Cambridge University Press, 2011.

3. Online Computation and Competitive Analysis, Allan Borodin and Ran El-Yaniv, 2005.

4. Approximation Algorithms, V. Vazirani, Springer-Verlag, 2004.

5. Computer Algorithms- Introduction to Design & Analysis, Sara Baase, Allen Van Gelder,

Addison-Wesley, 3rd Edition, 1999.

CSE 5102: Combinatorial Optimization

Credit Hour: 3.00

Prerequisite: None

Introduction to Optimization; Linear Programming: Different forms, Simplex Method, Primal-

Dual theory; Max-Flow: The Max-Flow-Min-Cut Theorem, Ford-Fulkerson Labeling Algorithm,

Dijkstra's Algorithm, The Floyd-Warshall Algorithm; Some Network Flow Algorithms: The

Minimum Cost Network Flow Method, Transportation Problem; Capacitated Transportation

Problem, Assignment Problem; Integer Linear Programming; Relaxation; Cutting-Plane

Algorithm; Branch and Bound Technique; Dynamic Programming; NP-Completeness; TSP and

Heuristics; Approximation.


1. The Design of Approximation Algorithms, David P. Williamson, David B. Shmoys,


2. Combinatorial Optimization Algorithms and Complexity, C.H. Papadimitrion, Dover

Publications, Unabridged Edition, 1998.

3. Discrete and Combinatorial Mathematics, Ralph P. Grimaldi, Pearson Education, 5th

Edition, 2003.

4. Combinatorial Optimization: Theory and Algorithms, By Bernhard Korte, Jens Vygen,

Springer, 4th Edition, 2007.

CSE 5103: Graph Theory

Credit Hour: 3.00

Prerequisite: None



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Introduction, Fundamental concepts, Trees, Spanning trees in graphs, Distance in graphs,

Eulerian graphs, Digraphs, Matching and factors, Cuts and connectivity, k-connected graphs,

Network flow problems, Graph coloring: vertex coloring and edge coloring, Line graphs,

Hamiltonian cycles, Planar graphs, Perfect graphs.


1. Introduction to Graph Theory, Douglas B. West, Pearson Education, 2nd Edition, 2000.

2. Discrete Mathematics with Graph Theory, Ddgar G. Goodaire, Michael M. Parmenter,

Pearson Education, 3rd Edition, 2005.

3. Graph Theory with Applications to Engineering and Computer Science, Narsingh Deo,

Prentice-Hall of India Pvt.Ltd, 2004.

4. Extremal Combinatorics, S. Jukna, Springer-Verlag, Berlin, 2000.

CSE 5104: Computational Geometry

Credit Hour: 3.00

Prerequisite: None

Searching and Geometric Data Structures: Balanced binary search trees, Priority-search trees,

Range searching, Interval trees, Segment trees, Algorithms and complexity of fundamental

geometric objects: Polygon triangulation and art gallery theorem, Polygon partitioning, Convex-

hulls in 2-dimension and 3-dimension, Dynamic convex-hulls; Geometric intersection: Line

segment intersection and the plane-sweep algorithm, Intersection of polygons; Proximity:

Voronoi diagrams, Delunay triangulations, closest and furthest pair; Visualization: Hidden

surface removal and binary space partition (BSP) trees; Graph Drawings: Drawings of rooted

trees (Layering, Radial drawings, HV-Drawings, Recursive winding), Drawings of planar graphs

(Straight-line drawings, Orthogonal drawings, Visibility drawings); Survey of recent

developments in computational geometry.


1. Computational Geometry and Computer Graphics in C++, Michael J. Laszlo, Prentice

Hall, 1st Edition, 1995.

2. Planner Graph Drawing, Takao Nishizeki, Md. Saidur Rahman, World Scientific, 2004.

3. Graph Drawing: Algorithms for the Visualization of Graphs, Giuseppe Di Battista, Peter

Eades, Roberto Tamassia, Ioannis G. Tolli, Prentice Hall, 1999.

4. Computational Geometry: Algorithms and Applications, Mark de Berg, 3rd Edition,

Springer, 2008.

5. Computational Geometry: An Introduction, Franco P. Preparata, Michael Shamos,

Springer, 1993.

CSE 5105: Bioinformatics Algorithms

Credit Hour: 3.00

Prerequisite: None

Introduction; Molecular biology basics: DNA, RNA, genes, and proteins; Restriction mapping

algorithm; Motif in DNA sequences, motif finding algorithms; Genome rearrangements, sorting

by reversals and breakpoints; DNA sequence alignments; Gene prediction; Space-efficient

sequence alignments, sub-quadratic alignment; DNA sequencing, genome sequencing, protein

sequencing, spectrum graphs; Combinatorial pattern matching: Exact pattern matching, heuristic

similarity search algorithms, approximate string matching, BLAST, FASTA; Clustering:

Microarrays, hierarchical clustering, K-means clustering, corrupted cliques problem, CAST

clustering algorithm; Evolutionary trees.



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1. Bioinformatics Computing, Bryan Bergeron, Prentice Hall, 1st Edition, 2002.

2. Introduction to Bioinformatics, T.K. Attwood, D.J. Parry-Smith, Pearson Education, 1st

Edition, 1997.

3. An Introduction to Bioinformatics Algorithms, By Neil C. Jones, Pavel Pevzner, The

MIT Press, 1st Edition, 2004.

4. Bioinformatics: A practical guide to the analysis of genes and proteins, A.D. Baxevanis

and B.F.F. Ouellette (ed.), John Wiley & Sons, 3rd

edition. 2004.

5. Biological sequence analysis, Probabilistic Models of Proteins and Nucleic Acids,

Richard Durbin, Sean R. Eddy, Anders Krogh, and Graeme Mitchison, Cambridge

University Press, 1998.

CSE 5106: Stringology

Credit Hour: 3.00

Prerequisite: None

Introduction to Stringology: Notations, Problems and Naive Solutions, Motivations,

Applications, Basic string searching algorithms; Data structures for String Matching: Suffix

Tree, Suffix Array, Aho-Corasick Automaton, Applications of these data structures;

Approximate Pattern Matching: Edit distance, Dynamic programming, Similarity measures for

DNA and protein sequences, q-gram methods, Bit-parallel methods, Algorithms for

degenerate/indeterminate strings; Sequence Analysis: Longest Common subsequence (LCS)

Problem, Advanced Algorithms for LCS, Variants of LCS and algorithms; Text Compression:

Shannon-Fano and Huffman codes, Arithmetic coding, Lempel-Ziv family of compression

techniques, Burrows-Wheeler Transformation.


1. Algorithms on Strings, Maxime Crochemore, Christophe Hancart, Thierry lecroq,


2. Grammatical Inference: Learning Automata and Grammars, Colin de la Higuera,


3. Computing Patterns in Strings, Bill Smyth Pearson/Addison-Wesley, 2003.

4. Flexible pattern matching in strings: Practical On-Line Search Algorithms for Texts and

Biological Sequences, Gonzalo Navarro, Mathieu Ranot, Cambridge University Press,

2007.

5. Jewels of Stringology: Text Algorithms, Maxime Crochemore, Wojciech Rytter, World

Scientic Publishing, 2002.

CSE 5107: Mathematical Programming

Credit Hour: 3.00

Prerequisite: None

Basic concept of Mathematical Programming, Concepts of linear and quadratic programming,

Convexity, Convex sets and convex functions, Concept of integer programming, Some examples

of integer programming problems, Linear programming techniques, Graphical solution of linear

programming problems, Simplex method, Dual simplex method, Different integer programming

techniques, Revised simplex method.


1. Mathematical Programming: Theory and Methods, S. M. Sinha, Elsevier, 2005.



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2. Mathematical Programming, Kenneth D. Lawrence Emerald Group Publishing Limited,

2004.

3. Mathematical Programming, Steven Vajda Dover Publications, 2009.

4. Introduction to Linear Optimization, Dimitris Bertsimas, and John Tsitsiklis, Athena

Scientific, 1997.

CSE 5108: Petri Net Theory and Modeling of Systems

Credit Hour: 3.00

Prerequisite: None

Introduction to Petri Nets, Elementary Net Systems, Place/Transition Nets, Definition and types

of Petri nets, Terms and notations marking, Importance of net theory, Transition firings, Practical

modeling examples, Introduction to workflow, workflow modeling using Petri Nets, Liveness

and safeness, Behavioral properties, Deadlocks and siphons, Structural properties, Colored Petri

Nets, Time Petri Nets, Timed Petri Nets, Stochastic Petri Nets.


1. Hardware Design and Petri Nets, Edited by Alex Yakovlev, Luis Gomes, Luciano

Lavagno, Springer, 2000.

2. Modeling in Systems Biology: The Petri Net Approach, Ina Koch, Wolfgang Reisig, Falk

Schreiber, Springer, 2011.

3. Petri Net Technology for Communication-Based Systems: Advances in Petri Nets,

Hartmut Ehrig, Wolfgang Reisig, Grzegorz Rozenber, Herbert Weber, Springer, 2003.

CSE 5151: Cryptography

Credit Hour: 3.00

Prerequisite: None

Classical Cryptography; Data Encryption Standard, Advance Encryption Standard; Public-key

cryptography: RSA cryptosystem, ElGamal cryptosystem; Signature Schemes: ElGamal

signature schemes, Digital signature standard; Hash Functions: Collision-free Hash functions;

Key Distribution and Key Agreement: Key pre-distribution, Diffie-Hellman key exchange;

Identification Schemes: Schnorr identification scheme, Okamoto identification schemes;

Algorithm to compute discrete logs; Chinese Remainder method, Polard’s rho method; Attacks:

Brute Force attack, Birthday attack; Cryptanalysis: Linear cryptanalysis, Differential

cryptanalysis; Elliptic Curves; Quantum cryptography;


1. Foundations of Cryptography: Basic Tools, O. Goldreich, Cambridge University Press,

2001.

2. Cryptography and Network Security, William Stallings, Pearson Education, 6th Edition,

2013.

3. Applied Cryptography, Bruce Sehneier, John Willey & Sons, 2nd Edition, 1996.

4. Cryptography Engineering: Design Principles and Practical Applications, Niels Ferguson,

Bruce Schneier, Tadayoshi Kohno, Wiley Publishing, Inc., 1st Edition, 2010.



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Software Engineering and Information Systems

CSE 5201: Advanced Software Engineering

Credit Hour: 3.00

Prerequisite: None

Introduction to Software Engineering, Unified Modeling Language, Requirements Engineering,

Design, Testing, Software Lifecycle, Refactoring, Extreme Programming, Requirements

Engineering, Software Architecture, Service Oriented Architecture, Model Driven Architecture,

Aspect Oriented Software Development, Software Processes.


1. Software Engineering: A Practitioner's Approach, Roger Pressman, Bruce Maxim, 8th

Edition, 2014.

2. Fundamentals of Software Engineering, Carlo Ghezzi, Mehdi Jazayeri Dino Mandrioli,

Prentice Hall, 2nd Edition, 2002.

3. Object Oriented Software Engineering using UML, Patterns, and Java, Bernd Bruegge,

Allen H. Dutoit, Prentice Hall, 3rd Edition, 2009.

CSE 5202: Software Project Management

Credit Hour: 3.00

Prerequisite: None

Foundations of software project management; organization structure and staffing; motivation,

authority and influence; conflict management; proposal preparation; a large engineering software

system management; client management; managing software project teams; project planning and

scheduling; risk management; configuration management; pricing estimation and cost control;

quality assurance and accreditation; factors affecting software quality; software quality assurance

plans; business context and legal issues for software projects; software measurement: testing,

upgrading and maintenance; network systems; and international project management.


1. Software Project Management: A Concise Study, S. A. Kelkar, Prentice Hall of India,

2nd Edition, 2009.

2. Software Project Management: A Unified Framework, Walker Royce, Addison-Wesley

Professional, 1st Edition, 1998.

3. Software Project Management in Practice, Pankaj Jalote, Pearson Education, 2002.

CSE 5203: Software Testing and Quality Assurance

Credit Hour: 3.00

Prerequisite: None

Definition and concept of software quality assurance (SQA); quality models; specification of

quality requirements; product development & delivery issues; software development processes &

maturity; software quality management process: total quality management, improvement cycle,

SQA planning & management, organizing the SQA effort; software verification & validation;

typical software development errors; Fagan inspections; software audit; software testing: testing

objectives & testing fundamentals, testing theory, coverage criteria, equivalence class testing,

value-based testing, decision table, syntax & state transition testing, statement & path testing,

branch & condition testing, data flow testing, thread-based testing, integration & integration

testing, system testing; testing in object-oriented systems; test tools & test automation; test

management; problem reporting & corrective action.



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1. Foundations of Software Testing, Aditya P. Mathur, Addison-Wesley Professional, 2nd

Edition, 2014.

2. Software Testing: Principles and Practices, Srinivasan Desikan, Gopalaswamy Ramesh,

Pearson Education, 1st Edition, 2006.

3. Handbook of Software Quality Assurance, G. Gordon Schulmeyer, Artech House

Publishers, 4th Edition, 2007.

CSE 5204: Software Verification and Validation Tools

Credit Hour: 3.00

Prerequisite: None

Introduction to automated verification and validation of software, test execution systems,

performance measurement tools, testing graphical user interfaces, coverage measurement and

tools, web application testing, software security testing, introduction to model checking,

verification tools (SMV, SPIN, DiVinE).


1. Software Verification and Validation: A Practitioner's Guide, Steven R. Rakitin Artech

House: A Practitioner's Guide, Steven R. Rakitin, Artech House Publishers, 1997.

2. Software Verification and Validation: An Engineering and Scientific Approach, Marcus

S. Fisher, Springer, 2007.

3. Verification and Validation of Modern Software-intensive Systems, G. Gordon

Schulmeyer, Garth R. MacKenzie, Prentice Hall, 1st Edition, 2000.

CSE 5251: Advanced Database Systems

Credit Hour: 3.00

Prerequisite: None

Object Oriented Database; Data Model, Design, Languages; Object Relational Database:

Complex data types, Querying with complex data types, Design; Distributed Database: Levels of

distribution transparency, Translation of global queries to fragment queries, Optimization of

access strategies, Management of distributed transactions, Concurrency control, Reliability,

Administration; Parallel Database: Different types of parallelism, Design of parallel database;

Multimedia Database SystemsBasic concepts, Design, Optimization of access strategies,

Management of Multimedia Database Systems, Reliability; Database Wire-housing/Data mining:

Basic Concepts and algorithms.


1. Fundamentals of Database Systems, Ramez Elmasri, Pearson Education, 5th Edition,

2006.

2. Object-Oriented Database Systems: Approaches and Architectures, C.S.R. Prabhu,

Prentice Hall of India, 2nd Edition, 2005.

3. Database Systems The Complete Book, Hector Garcia-Molina, Jeffrey D. Ullman,

Jennifer Widom, Pearson Education, 2nd Edition, 2008.

CSE 5252: Information System Management

Credit Hour: 3.00

Prerequisite: None



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Information systems management: importance of information systems (IS) management, IS

management's leadership role, strategic uses of IT, IS planning; managing essential technologies:

distributed systems, managing telecommunications, managing information resources, and

managing operations; managing system development: technologies for developing systems and

management issues in system development; systems for supporting knowledge work: supporting

decision making, collaboration, and knowledge works; acquisition of hardware, software,

networks, and services: request for proposal, acquisition methods (buy, rent, or lease), software

acquisition, and analysis of alternatives; people and technology: the challenges ahead.


1. Information Systems Strategic Management: An Integrated Approach, Steve Clark,

Routledge, 2nd Edition, 2006.

2. Outsourcing Management Information Systems, Edited by Marc J. Schniederjans, Ashlyn

M. Schniederjans, Idea Group Inc (IGI), 2007.

3. Management Information Systems, S. Shajahan, New Age International, 2004.



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Communications and Computer Networks

CSE 5301: Computer Communications and Networks

Credit Hour: 3.00

Prerequisite: None

Modifications of TCP; TCP over ATM; ATM internetworking; ATM service categories and

quality of services; ATM switch architectures and their performance; Digital switching; Traffic

analysis; Fiber optics networks optical packet switching; Metropolitan networks, Wide area

networking, Gigabit Ethernet, ADSL.

HTTP, pHTTP and recent advances in internet protocols; Web server performance, proxy

servers, load balancing in web servers; IP switching: Tag switching, Multi-protocol label

switching; IP security; Queuing models for networks and protocols; Real time protocols: RTP,

RTCP, RTSP; Voice over IP; Distributed object technology for networking; Networks agents;

Active networks and protocol boosters, Multimedia Networking: Integrated Service, Differential

Service, MPLS.


1. Data and Computer Communications, William Stallings, Prentice Hall, 10th Edition,

2013.

2. Computer Networks, Andrew S. Tanenbaum, Prentice Hall, 5th Edition, 2010.

3. Computer Networks and Internets, Douglas E Comer, Addison-Wesley, 6th Edition,

2014.

CSE 5302: Wireless and Mobile Communication Networks

Credit Hour: 3.00

Prerequisite: None

Characteristics of cellular communications; QOS in cellular communications; Wireless LAN;

Wireless ATM and media access protocols for WATM; Wireless application protocols; Wireless

personal communications; Mobile IP; Spread spectrum techniques: DSSS, FHSS, CDMA, GSM,

CPDP; satellite communications; internetworking via satellites; Mobile satellite

communications.


1. Mobile Communications, Jochen Schiller, Addison-Wesley, 2nd Edition, 2003.

2. Ad Hoc Wireless Networks: Architectures and Protocols, C. Siva Ram Murthy, B.C.

Manoj, Prentice Hall, 1st Edition, 2004.

3. Wireless Communication Systems: Advanced Techniques for Signal Reception,

Xiaodong, Wang H., Vincent Poor, Prentice Hall, 1st Edition, 2003.

CSE 5303: Wireless Ad Hoc Networks

Credit Hour: 3.00

Prerequisite: None

Introduction: applications and motivations; broadcasting protocols: algorithmic aspect,

optimization techniques, power-efficient broadcasting;, routing protocols: DSDV, AODV, DSR,

position based routing protocols, load balancing techniques, multi-path routing; medium access

control protocols: reservation-based MAC protocols, Bluetooth technology, IEEE 802.11 based

MAC protocols; channel propagation models; topology control protocols; power aware protocol

design; cross layer design principles; mobility awareness; fairness and security issues: attacks



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and preventions; stimulating cooperation: self policing schemes, economic incentive based

schemes; other state-of-the-art relevant topics.


1. Ad Hoc Wireless Networks: Architectures and Protocols, C. Siva Ram Murthy, B.C.

Manoj, Prentice Hall, 1st Edition, 2004.

2. Guide to Wireless Ad Hoc Networks, Edited by Sudip Misra, Isaac Woungang, Subhas

Chandra Misra, Springer, 2009.

3. Ad Hoc Wireless Networking edited by Xiuzhen Cheng, Xiao H. Huang, Ding-Zhu Du,

Springer, 2004.

CSE 5304: Wireless Sensor Networks

Credit Hour: 3.00

Prerequisite: None

Introduction: applications; Localization and tracking: tracking multiple objects; Medium Access

Control: S-MAC, IEEE 802.15.4 and ZigBee; Geographic and energy-aware routing; Attribute-

Based Routing: directed diffusion, rumor routing, geographic hash tables; Infrastructure

establishment: topology control, clustering, time synchronization; Sensor tasking and control:

task-driven sensing, information-based sensor tasking, joint routing and information aggregation;

Sensor network databases: challenges, querying the physical environment, in-network

aggregation, data indices and range queries, distributed hierarchical aggregation; Sensor network

platforms and tools: sensor node hardware, sensor network programming challenges; Other state-

of-the-art related topics.


1. Wireless Sensor Networks: An Information Processing Approach, By Feng Zhao,

Leonidas J. Guiba, Morgan Kaufmann, 1st Edition, 2004.

2. Protocols and Architectures for Wireless Sensor Networks, By Holger Karl, Andreas

Willig, Wiley Publishers, 2005.

3. Wireless Sensor Networks and Applications, By Yingshu Li, My T. Thai, Springer, 2008.

CSE 5305: Wireless Resource Management

Credit Hour: 3.00

Prerequisite: None

Resource management architecture: evolution and components of QoS and cross-layer

architecture for bandwidth management; tri-band and smart antenna; handoff management;

mobility prediction; resource management and connection admission control; bandwidth

allocation and scheduling: real-time guaranteed and fair real-time scheduling; inter-domain radio

resource management; high performance broadband architecture; wireless truthful computing;

resource allocation of spatio-temporal division multiple access control; resource management

schemes for connectivity: Piconet and scatternet; energy efficient MAC layer protocols for

wireless ad-hoc networks; routing and resource discovery for wireless ad-hoc networks: QoS

based routing, topology management, efficient resource discovery, hybrid routing protocols, and

localization; energy efficient broadcasting and multicasting algorithms; power-conserving

broadcasting and multicasting algorithms; scopes of increasing wireless resources, research and

future developments.


1. Wireless Communications Resource Management, Byeong Gi Lee, Daeyoung Park,

Hanbyul Seo, Wiley Publishers; 1st Edition, 2008.

2. Practical Radio Resource Management in Wireless Systems, By Sofoklis A. Kyriazakos,

George T. Karetsos, Artech House INC, 2004.



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3. Wireless Information Networks: Architecture, Resource Management, and Mobile Data,

Jack M. Holtzman, Springer, 1996.

CSE 5306: Network Security

Credit Hour: 3.00

Prerequisite: None

Issues of Network security, treats to network security: wiretapping, impersonation, hacking,

cracking, phishing, ID theft, authentication and authorization, firewalls, Virtual private networks,

intrusion detection system; Secure network devices; security policies ; internet vulnerabilities;

Web security, e-mail security, e-commerce security.


1. Cryptography and Network Security, William Stallings, Prentice Hall, 6th Edition, 2013.

2. Java 2 Network Security, Marco Pistola, Duane F. Reller, Deepak Gupta, Milind Nagnur,

2nd Edition, 1999.

3. Network Security Architectures, Sean Convery, Cisco Press, 1st Edition, 2004.



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Intelligent Systems

CSE 5401: Advanced Artificial Intelligence

Credit Hour: 3.00

Prerequisite: None

Introduction, Advanced search techniques in AI, Knowledge based system design, Advanced

plan generating systems, Bayesian network and probabilistic reasoning, Learning in neural belief

networks, Practical natural language processing, Computer vision, Introduction to Robotics.


1. Advanced Artificial Intelligence, Zhongzhi Shi, World Scientific Publishing Company,

2011.

2. Artificial Intelligence: A Modern Approach, Stuart Jonathan Russell, Peter Norvig,

Prentice Hall, 3rd Edition, 2009.

3. Artificial Intelligence: A Guide to Intelligent Systems, Michael Negnevitsky, Pearson

Education Canada, 3rd Edition, 2011.

CSE 5402: Fuzzy Systems

Credit Hour: 3.00

Prerequisite: None

Basic Concepts of Fuzzy set theory; Fuzzy numbers; Aggregation operations of Fuzzy sets; The

theory of approximate reasoning; Introduction to Fuzzy logic control; Fuzzy System Models and

Developments; Fuzzy logic controllers; Defuzzification methods; Linguistic descriptions and

their analytical forms; The flexible structure of fuzzy systems; Practical Aspects of Neural

Networks.


1. Neural Networks and Fuzzy Systems: A Dynamical Systems Approach to Machine

Intelligence/Book and Disk, Bart Kosko, Prentice Hall, Har/Dis Edition, 1991.

2. Introduction to Neuro-Fuzzy Systems, By Robert Fuller, Springer, 2000.

3. Fuzzy systems design principles: building Fuzzy IF-THEN rule bases, Riza C. Berkan,

Sheldon L. Trubatch, Wiley-IEEE Press, 1st Edition, 1997.

CSE 5403: Machine Learning

Credit Hour: 3.00

Prerequisite: None

Definition of learning systems, Goals and applications of machine learning, Inductive

Classification, Decision Tree Learning, Ensemble Learning, Experimental Evaluation of

Learning Algorithms, Computational Learning Theory, Rule Learning: Propositional and First-

Order, Artificial Neural Networks, Support Vector Machines, Bayesian Learning, Instance-

Based Learning, Text Classification, Clustering and Unsupervised Learning, Language Learning


1. Genetic Algorithms in Search, Optimization & Machine Learning, David E. Gold Berg,

Addison-Wesley Professional, 1st Edition, 1989.

2. Pattern Recognition and Machine Learning, Christopher M. Bishop, Springer, 2007.

3. Machine Learning: An Artificial Intelligence Approach, Volume 2, edited by Ryszard S.

Michalski, Ryszard Stanisław Michalski, Jaime Guillermo Carbonell, Tom Michael

Mitchel, Morgan Kaufmann, 1982.



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CSE 5404: Advanced Pattern Recognition

Credit Hour: 3.00

Prerequisite: None

Introduction to formal languages, String languages for pattern description, Higher dimensional

pattern grammars, Syntax analysis as a recognition procedure, Stochastic languages, Error-

correcting parsing for string languages, Error-correcting tree automata, Cluster analysis for

syntactic patterns, Grammatical inference for syntactic pattern recognition, Application shape

analysis of wave forms and contours, Syntactic approach to texture analysis.


1. Pattern recognition: Statistical, Structural, and Neural Approaches, Robert J. Schalkoff, J.

Wiley, 1992.

2. Pattern Recognition and Image Analysis, Earl Gose, Richard Johnsonbaugh, Steve Jost,

Prentice Hall, Har/Dsk Edition, 1996.

3. Advanced Pattern Recognition Technologies with Applications to Biometrics, David

Zhang, Fengxi Song, Yong Xu, Zhizhen Liang, Medical Information Science Reference,

1st Edition, 2008.

CSE 5405: Speech Recognition

Credit Hour: 3.00

Prerequisite: None

Introduction, Speech signal: production, perception and characterization, Signal processing and

analysis; Pattern comparison techniques: distortion measures, spectral-distortion measures, time

alignment and normalization; Recognition system design and implementation: source-coding,

template training, performance analysis; Connected word models: two level DP, level building

algorithm, one-pass algorithm; Continuous speech recognition: sub word units, statistical

modeling, context-dependent units; Task oriented models.


1. Fundamental of Speech Recognition, Lawrence Rabiner, Biing- Hwang Juang, Prentice

Hall, 1st Edition, 1993.

2. Advances in Speech Recognition: Mobile Environments, Call Centers and Clinics, Amy

Neustein, Springer, 2010.

3. Computer Speech: Recognition, Compression, Synthesis, Manfred R. Schroeder,

Springer, 1999.

CSE 5406: Machine Translation

Credit Hour: 3.00

Prerequisite: None

Theoretical problems: Definition, Context dependency, interpretation and translation;

Engineering problems of machine translation: Maintainability, tunability, modularity, and

efficiency; Linguistics-based MT: Compositionality and isomorphism, Declarative frameworks,

Constraint-based formalisms; Knowledge-based MT: Translation and understanding, Design of

interlinguas, The conceptual lexicon; Statistics-based MT: E-M algorithms, Alignment of

bilingual corpora, Translation templates; Example-based MT: Similarity measures, Levels of

comparison; Treatment of context dependency: Knowledge-based transfer, Sublanguage-based

MT, Translation units.


1. Machine Translation: Its Scope and Limits, Yorick Wilks, Springer, 1st Edition, 2010.



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2. Learning Machine Translation, edited by Cyril Goutte, Nicola Cancedda, Marc

Dymetman, George Foster, The MIT Press, 2008.

3. Logic Programming, Knowledge Representation, and Nonmonotonic Reasoning, edited

by Marcello Balduccini, Tran Cao Son, Springer, 2011.

CSE 5407: Knowledge Representation and Reasoning

Credit Hour: 3.00

Prerequisite: Basic course on Logic/AI

Knowledge representation, uses in computers; logic-based languages for KR; automated

reasoning techniques and systems; applications of KR to ontologies and semantic web.


1. Knowledge Representation and Reasoning, Ronald J. Brachman, Hector J. Levesque,

Morgan Kaufmann, 1st Edition, 2004.

2. Foundations of Knowledge Representation and Reasoning, edited by Gerhard

Lakemeyer, Bernhard Nebel, Springer, 1994.

3. Knowledge Representation, Reasoning and Declarative Problem Solving, Chitta Baral,

Cambridge University Press, 1st Edition, 2010.

CSE 5408: Advanced Data Mining

Credit Hour: 3.00

Prerequisite: None

Introduction; Data warehousing and OLAP technology for data mining; Data preprocessing;

Data mining primitives, languages and systems; Descriptive data mining: characterization and

comparison; Association analysis; Classification and prediction; Cluster analysis; Mining

complex types of data; Applications and trends in data mining.


1. Principles of Data Mining, David Hand, Heikki Mannila, Padhraic Smyth, A Bradford

Book, 2001.

2. Data Mining Introductory and Advanced Topics, Margaret H. Dunham, Pearson

Education, 2006.

3. Data Mining: Next Generation Challenges and Future Directions, Hillol Kargupta,

Anupam Joshi, Krishnamoorthy Sivakumar, Yelena Yesha, MIT Press Ltd, 2004.

CSE 5451: Evolutionary Algorithms

Credit Hour: 3.00

Prerequisite: None

Introduction to evolutionary algorithm; Selection: rank-based, roulette wheel, stochastic, local,

truncation and tournament; Recombination: discrete, real valued and binary valued; Mutation:

real valued and binary valued; Reinsertion: global and local; Population models: global-

worker/farmer, local – diffusion, and regional – migration; Co-evolution: cooperative and

competitive; Learnable evolution model; Fast evolutionary programming; Application of

evolutionary algorithms to: system design, telecommunication, robotics and other industrial

areas.


1. Evolutionary Algorithms in Engineering Applications, edited by Dipankar Dasgupta,

Zbigniew Michalewicz, Springer, 1997.

2. Evolutionary Algorithms for Solving Multi-Objective Problems, Carlos Coello Coello,

Gary B. Lamont, David A. van Veldhuizen, Springer, 2nd Edition, 2007.



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3. Multi-Objective Optimization Using Evolutionary Algorithms, Kalyanmoy Deb, Wiley

Publishers, 1st Edition, 2009.

CSE 5452: Neural Networks

Credit Hour: 3.00

Prerequisite: None

Fundamentals of Neural Networks; Back propagation and related training algorithms; Hebbian

learning; Cohonen-Grossberg learning; The BAM and the Hopfield Memory; Simulated

Annealing; Different types of Neural Networks: Counter propagation, Probabilistic, Radial Basis

Function, Generalized Regression, etc; Adaptive Resonance Theory; Dynamic Systems and

neural Control; The Boltzmann Machine; Self-organizing Maps; Spatiotemporal Pattern

Classification, The Neocognition; Practical Aspects of Neural Networks.


1. Neural Networks and Fuzzy Systems: A Dynamical Systems Approach to Machine

Intelligence/Book and Disk, Bart Kosko, Prentice Hall, Har/Dis Edition, 1991.

2. Fundamentals of Artificial Neural Networks, Mohamad H. Hassoun, A Bradford Book,

2003.

3. Understanding Neural Networks and Fuzzy Logic, Stamatios V. Kartalopoulos, Wiley-

IEEE Press, 1st Edition, 1995.



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Multimedia Technology

CSE 5501: Multimedia Systems

Credit Hour: 3.00

Prerequisite: None

Overview to Multimedia Systems, Multimedia storage, Data compression techniques for audio

and video, Synchronization, Multimedia networking and protocols, QOS principles, Video

streams on ATM, Mobile multimedia communications, Operating system support for

multimedia, Hypermedia system, Standards for multimedia, Multimedia database and

Multimedia Applications.

Multimedia data: image, audio, and video; Image encoding: Transform coding, vector

quantization, and Fractal encoding; Image encoding standards; Audio encoding: Liner predictive

coding, filter bank design, psychoacoustic models, Code Excited Linear Prediction (CELP),

Algebraic CELP, Regular Pulse Excitation, Multi Pulse Excitation, and Vector-sum Excited

Linear Prediction ; Audio encoding standards; Video encoding: motion prediction (full search, ½

pel and ¼ pel precision), and Fine-granular scalable encoding (Bit-plane encoding); Video

encoding standards; Video file formats; Video storage mediums; Audio-video Channel coding.


1. Multimedia Systems, Ralf Steinmetz, Klara Nahrstedt, Springer Berlin Heidelberg, 2010.

2. Introduction to Multimedia Systems, Urbashi Mitra, Academic Press, 2004.

3. Managing Multimedia: Project Management for Interactive Media, Elaine England and

Andy Finney, Addison Wesley, 2nd Edition, 1998.

4. Multimedia Systems, John F. Koegel Buford, Addison-Wesley Professional, 1994.

CSE 5502: Computer Graphics and Animation

Credit Hour: 3.00

Prerequisite: None

Advanced Graphic Techniques: Graphics basics, Three dimensional drawings, Geometric forms

and models, Hidden surfaces, Fractals; Advanced rendering Techniques: Shadow generation

techniques, Texture and environment mapping techniques, Procedural texture mapping and

modeling, Ray tracing, Radiosity methods, Global illumination models, Volume rendering

techniques; Advanced Animation: Animation articulated structures, Soft object animation,

Procedural animation.


1. Computer Graphics Using Open GL, F.S. Hill, Jr., Prentice Hall, 2nd Edition, 2000.

2. Computer Graphics Multimedia And Animation, Malay K.. Pakhira, PHI Learning, 2010.

3. Computer Graphics with OpenGL, Donald D. Hearn, M. Pauline Baker, Prentice Hall,

3rd Edition, 2003.

CSE 5503: Human Computer Interaction

Credit Hour: 3.00

Prerequisite: None

Psychopathology of everyday things: visibility, affordances, natural mapping; psychology of

everyday actions: seven stages of action gulf of execution and evaluation; knowledge in the head

and in the world; constraints; human errors; design challenges; user-centered design; Cognetics

and locus of attention; meaning, modes, monotony, myths; quantification; unification;

navigation.



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1. Human-Computer Interaction, Alan Dix, Janet Finlay Gregory, D. Abovod, Russell

Beale, Prentice Hall, 3rd Edition, 2003.

2. Human-Computer Interaction in the New Millennium, John M. Carroll, Addison-Wesley

Professional, 1st Edition, 2001.

3. Interaction Design: Beyond Human - Computer Interaction, Yvonne Rogers, Helen

Sharp, Jenny Preece, Wiley Publishers, 3rd Edition, 2011.

CSE 5504: Multimedia Communication Credit Hour: 3.00

Prerequisite: None

Multimedia information representation, Multimedia networks, Multimedia services and

applications, Network QoS and application QoS, Transform coding, Motion compensated

predictive coding; Information representation: text, image, audio and video; Text and image

compression: compression principles, text compression, image compression; Audio and Video

compression: Audio compression, Video compression, Video compression principles;

Multimedia compression standards: JPEG, H.26x, MPEG 1/2/4/7, AVC, Scalable Video Coding;

Other coding formats for text, speech, image and video; Multimedia communication across

networks: Layered video coding, Error relevant video coding techniques, Multimedia transport

across IP networks and relevant products such as RSVP, RTP, RTCP, DVMRP, Multimedia in

mobile networks, Multimedia broadcast networks, Content based retrieval in digital libraries;

End-to-End QoS for video delivery, Wireless video, Error control in video streaming, Cross-

layer video adaptation.


1. Multimedia Communications, Jerry D. Gibson, Academic Press, 2000.

2. Multimedia Communication Systems: Techniques, Standards, and Networks, K.R. Rao,

Zoran S. Bojkovic, Dragorad A. Milovanovic, Prentice Hall, 1st Edition, 2002.

3. Multimedia Communications- Applications, Networks, Protocols and Standards, Fred

Halsall, Addison-Wesley, 1st Edition, 2000.



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High-performance Computing

CSE 5601: Parallel Algorithms

Credit Hour: 3.00

Prerequisite: None

Introduction, Parallel processing, Parallel models, Performance of Parallel Algorithms, The

work-time presentation framework, Basic techniques: Pointer jumping, Balanced trees, Divide

and Conquer, Pipelining, Partitioning and symmetry breaking, List ranking, Euler-Tour

technique, Tree contraction; Parallel searching, merging, sorting and selection, Connected

components, Minimum spanning trees, Biconnected Components, Directed graphs, Plane

sweeping, Visibility problems, Simulation between PRAM models, Lower hounds for EREW,

CREW and CRCW PRAMs.


1. Introduction to Parallel Algorithms, C. Xavier, S. S. Iyengar, Wiley-Interscience, 1st

Edition, 1998.

2. Parallel algorithms, Henri Casanova, Arnaud Legrand, Yves Robert, Chapman and

Hall/CRC, 2008.

3. Efficient Parallel Algorithms, Alan Gibbons, Wojciech Rytter, Cambridge University

Press, 1989.

4. Parallel Computer Architecture: A Hardware/Software Approach, David E. Culler,

Jaswinder Pal Singh, and Anoop Gupta, Morgan Kaufmann Publishers, 1998.

CSE 5602: Distributed Computing Systems

Credit Hour: 3.00

Prerequisite: None

Distributed object systems, Retrieving and caching of distributed information, Distributed data

replication and sharing, Performance issues, Algorithms for deadlock detection, Concurrency

control and synchronization in distributed system, Models for distributed computation,

Networking facilities and resource control and management methods in network and distributed

operating systems, Collaborative applications, Wide area network computing, Web based

commerce, Agent systems and Market based computing.

Large-scale distributed systems: properties and examples; search requirements in service

discovery, peer-to-peer content sharing and distributed XML databases; unstructured techniques:

intelligent flooding, hint-based routing, etc.; basic structured techniques: Chord, CAN, Tapestry,

Kademlia, etc.; advanced structured techniques: pSearch, Squid, SkipNet, etc.; Signature search

techniques using Bloom filters; Distributed Pattern Matching (DPM) problem and its

applications; distributed crawling and indexing techniques.


1. Energy Efficient Distributed Computing Systems, Albert Y. Zomaya, Young Choon Lee,

Wiley-IEEE Computer Society Press, 1st Edition, 2012.

2. Data Networks, Dimitri, and Robert Gallager, Upper Saddle River, NJ: Prentice Hall, 2nd

Edition, 1991.

3. Programming Distributed Computing Systems: A Foundational Approach, Carlos A.

Varela, The MIT Press, 2013.

4. Distributed Computing: Principles, Algorithms, and Systems, Ajay D. Kshemkalyani,

Mukesh Singhal, Cambridge University Press, 2011.



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CSE 5603: Distributed Databases

Credit Hour: 3.00

Prerequisite: Undergraduate database course

Principles in the design and implementation of distributed databases and distributed transaction

processing systems. Topics include: distributed computing concepts, computing networks,

distributed and multi-database system architectures and models, atomicity, synchronization and

distributed concurrency control algorithms, data replication, recovery techniques, reliability in

distributed databases.


1. Principles of Distributed Database Systems, M. Tamer Ozsu, Patrick Valduriez, Springer,

3rd Edition, 2011.

2. Distributed Database Management Systems: A Practical Approach, Saeed K. Rahimi,

Frank S. Haug, John Wiley & Sons, 2010.

3. Distributed Databases, Stefano Ceri, Giuseppe Pelagatti, Tata McGraw-Hill Education,

1984.

4. Digital Communications, Proakis, J. G., MA: McGraw-Hill, 4th Edition, 2001.

CSE 5604: Ubiquitous Computing

Credit Hour: 3.00

Prerequisite: None

Introduction to Ubiquitous Computing; Ubiquitous Computing Visionaries: mouse, Parc, MIT;

Ethics; Privacy; Responsibility; Architecture: Autonomic Computing, Distributed Computing,

Cloud Computing, Peer to Peer; Mobility: Mobile Computation and Agents, Smart Places,

Wearable Computing; Service-Orientation; Sensors and Actuators; Ubiquitous environments;

Ubiquitous theory: Location, Spatial Databases, Topological Reasoning, Metadata, Security and

Privacy; Ambient Calculus; Relational Models; Specifications: UML, OMG, Ontologies;

Context Awareness: GPS, location and tracking; Applications: Smart Homes, Smart Workplaces,

Social Computing, Religious Computing, Health and Medical Computing, Science, Surveillance,

Monitoring, Navigation.


1. Ubiquitous Computing Fundamentals, edited by John Krumm, Chapman and Hall/CRC,

1st Edition, 2009.

2. Ubiquitous Computing: Smart Devices, Environments and Interactions, Stefan Poslad,

Wiley, 1st Edition, 2009.

3. Everyware: The Dawning Age of Ubiquitous Computing, Adam Greenfield, New Riders

Publishing, 1st Edition, 2006

4. Communication Systems Engineering, Proakis, J. G., and M. Salehi, 3rd

Edition,

Englewood Cliffs, NJ: Prentice-Hall, 2004.



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Hardware Systems

CSE 5701: Advanced Microprocessor

Credit Hour: 3.00

Prerequisite: None

Review of different microprocessors: 80486, 68040, V70, Gmicro processors; Comparing the

architectures: RISC and CISC; Instruction set of machines: SPARC, INTEL, and MIPS; Study of

microprocessors: Pentium II, Alpha 21064, MIS 6400, PA-RISC; Math coprocessors and

microprocessors.


1. The Intel Microprocessors 8086/8088, 80/86 80188 80286, 80386, 80486, Pentium and

Pentium Processor, Barry B, Brey, Prentice Hall, 8th Edition, 2008.

2. Microprocessor Architecture Program and Applications with the 8085, Ramesh S.

Ganokar, Prentice Hall College Div, 4th Sub Edition, 1998.

3. Microprocessors and Interfacing, Douglas V Hall, Glencoe McGraw-Hill, 2nd Sub

Edition, 1991.

CSE 5702: Advanced Logic Design

Credit Hour: 3.00

Prerequisite: None

Functional decomposition and Symmetric functions; Linear sequential machines; Reed-Muller

expansions and their minimizations; EXOR based logic design; self-timed circuits; asynchronous

design techniques; Digital logic circuit testing and testable design: testing of combinational and

sequential logic circuits, design for testability and built-in self test; Digital logic simulation;

Reverse logic synthesis.


1. Advanced Digital Logic Design: Using Verilog, State Machines, and Synthesis for

FPGAs, Sunggu Lee, Thomson, 2006.

2. Switching Theory and Logic Design, C V S Rao, Pearson Education, 2006.

3. Advanced Digital Logic Design: Using Verilog, State Machines, and Synthesis for

FPGAs Sunggu Lee, Cengage Learning, 1st Edition, 2005.

4. Digital Logic Design, Brian Holdsworth, Clive Woods, Newnes, 4th Edition, 2002.

CSE 5703: Computer Organization and Design

Credit Hour: 3.00

Prerequisite: None

Classification and addressing modes, Operands and Operations for Media and signal processing,

instructions for control flow, Encoding an instruction set. Pipelined and Superscalar processors,

Data hazards, Dynamic scheduling, Branch prediction, Hardware based speculation, Thread level

parallelism. ILP with software approaches: Compiler Techniques, static branch prediction, static

multiple issue, advanced compiler support for ILP. Basic Techniques of Integer Arithmetic,

Floating-point Arithmetic, Speeding up Integer Addition, Speeding up Integer Multiplication and

Division. Memory technology, RAIDs, organization for improving performance, Virtual memory

and protection, Cache organization, Reducing cache miss rate and penalty. Busses, Performance

measures, Designing I/O system, Reliability, Dependability and Availability. Symmetric shared

memory architectures, Cache coherence protocols, Distributed shared memory architectures,

Synchronization, Models for memory consistency, Multithreading. Interconnection Networks-



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Practical issues, Network on chip, Designing cluster. Advanced RISC, CISC and Embedded

processors architectures.


1. Computer Organization and Design: The Hardware/Software Interface, David A.

Patterson, John L. Hennessy, Morgan Kaufmann, 5th Edition, 2013.

2. Computer Organization & Architecture Designing for Performance, Prentice Hall, 9th

Edition, 2012.

3. Computer Organization and Design, P. Pal Chaudhuri, PHI Learning Private Limited, 3rd

Edition, 2013.

CSE 5704: Advanced Computer Architecture

Credit Hour: 3.00

Prerequisite: None

Measuring performance and cost: performance measurement, Benchmarks, costs of building

computers; Instruction sets: classifying instruction sets; improving CPU performance: pipelining,

dynamic instruction scheduling, branch prediction, instruction-level parallelism, VLIW

processor; vector processors: architecture and design, performance; memory hierarchy:

evaluation, cache design and optimization, virtual memory design, memory protection, memory

coherency; storage systems: reliability and availability, I/O system design; Multiprocessors:

parallel architecture classification, centralized vs distributed shared memory, interconnection

topologies, synchronization.


1. Advanced Computer Architecture, Kai Hwang, Tata Mcgraw-Hill Education, 2nd

Edition, 2011.

2. Computer Architecture and Parallel Processing, Kai Hwang, Mcgraw-Hill College, 1st

Edition, 1984.

3. Advanced Computer Architecture A Systems Design Approach, Richard Y. Kain,

Prentice Hall, 1st Edition, 1995.

4. Advanced Computer Architectures A Design Space Approach, Dezso Sima, Terence

Fountain, Peter Kacsuk, Addison-Wesley, 1st Edition, 1997.

CSE 5705: Embedded Systems

Credit Hour: 3.00

Prerequisite: None

Embedded computing, characteristics of embedded computing applications; embedded system

design; constraint-driven design; development environment: execution environment, memory

organization, system space, code space, data space, I/O space, start-up, interrupt response cycle,

function calls, runtime environment; computing platform: CPU bus, memory devices, I/O

devices, component interfacing; distributed embedded system design: inter-process

communication; networks for embedded system; Design techniques: design methodologies and

tools; system integration, structural and behavioral description.


1. Making Embedded Systems: Design Patterns for Great Software, Elecia White, O'Reilly

Media, 1st Edition, 2011.

2. Embedded Systems: Architecture, Programming And Design, Kamal Raj, Tata McGraw-

Hill Education, 2nd Edition, 2008.

3. Computer Organization & Architecture Designing for Performance, Prentice Hall, 9th

Edition, 2012.



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Special Topic

CSE 5999: Special Topic on X

Credit Hour: 3.00

Prerequisite: None

Remarks: ‘X’ will be a complete course name offered by the course teacher.



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CSE 6000: Master Thesis I (Research Proposal)

Credit Hour: 6.00

Prerequisite: CSE 5000: Scientific Research Methodology and CSE 5001: Seminar

Remark: Successful completion of this course leads a student to undertake the course CSE 6001:

Master Thesis II (Research) in the next term (with continue). Upon successful completion of

CSE 6001: Master Thesis II (Research), grade will be awarded for this course.

CSE 6001: Master Thesis II (Research)

Credit Hour: 12.00

Prerequisite: CSE 6000: Master Thesis I (Research Proposal)

CSE 6002: Master Project

Credit Hour: 6.00

Prerequisite: CSE 5000: Scientific Research Methodology and CSE 5001: Seminar

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